可解释性对用户接受AI用于知识创造的影响研究

胡保亮; 王嘉雯; 闫帅

doi:10.19571/j.cnki.1000-2995.2026.03.012

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科研管理 ›› 2026, Vol. 47 ›› Issue (3) : 117-127. DOI: 10.19571/j.cnki.1000-2995.2026.03.012 CSTR: 32148.14.kygl.2026.03.012

可解释性对用户接受AI用于知识创造的影响研究

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Research on the impact of explainability on users' acceptance of AI for knowledge creation

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摘要

人工智能（AI）黑箱问题正困扰着用户接受AI用于知识创造。可解释AI被认为是解决AI黑箱问题的重要方案之一。然而，现有研究鲜有探讨可解释性如何影响用户接受AI用于知识创造的机制。为此，本文着重研究了这一机制，这包括AI可解释性影响用户接受AI用于知识创造的路径机制以及用户特征对此路径的调节机制。本文提出了理论假设并对425份问卷数据进行了结构方程模型分析与层次回归分析，检验了相关假设。研究发现：可解释性的完整性、格式化与现时性维度对用户接受AI用于知识创造具有正向的影响；可解释性对用户接受AI用于知识创造的影响是间接的，需要感知有用性与感知易用性的中介。研究也发现：可解释性对用户接受AI用于知识创造的一些影响受学历、使用经验与职位等用户特征的调节。本文的结论由于为AI知识创造研究提供了一个基于可解释性的用户接受模型而对AI知识创造理论与可解释AI理论有贡献，也为企业正确发挥AI可解释性的作用、推进AI知识创造提供了启示。

Abstract

The black-box problem of artificial intelligence （AI） is troubling users to accept AI for knowledge creation. The explainable AI is one of the important solutions to solve the problem. However，existing literature has rarely explored how the explainability of AI affects users' acceptance of AI for knowledge creation. Therefore，this study focused on exploring the question，including the path mechanism of explainability affecting users' acceptance of AI for knowledge creation，and the moderating effect of user characteristics on the path. This paper proposed some theoretical hypotheses and conducted the structural equation modeling and hierarchical regression analysis on 425 questionnaire data to test the hypotheses. The results showed that the three dimensions of explainability，i.e.，completeness，format，and currency，have an influence on users' acceptance of AI for knowledge creation；the influence of explainability on users' acceptance of AI for knowledge creation is indirect，with perceived usefulness and perceived ease of use playing a mediating role. The results also showed that the influence of explainability on users' acceptance of AI for knowledge creation is moderated by user characteristics such as education level，usage experience，and position. This study will not only contribute to the theories of AI knowledge creation and AI explainability theory by providing a user acceptance model based on the explainability，but also provide insights for enterprises to correctly play the role of AI explainability and promote AI knowledge creation.

导出引用

胡保亮, 王嘉雯, 闫帅. 可解释性对用户接受AI用于知识创造的影响研究[J]. 科研管理. 2026, 47(3): 117-127 https://doi.org/10.19571/j.cnki.1000-2995.2026.03.012

Hu Baoliang, Wang Jiawen, Yan Shuai. Research on the impact of explainability on users' acceptance of AI for knowledge creation[J]. Science Research Management. 2026, 47(3): 117-127 https://doi.org/10.19571/j.cnki.1000-2995.2026.03.012

中图分类号： F270.7

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